Association between television in bedroom and adiposity throughout adolescence

Objective: The objective was to determine if having a television (TV) in the bedroom is associated with physical activity (PA), TV/video viewing, and adiposity throughout adolescence. Research Methods and Procedures: Longitudinal data (September 2002 through June 2005) were analyzed of 379 initially 12‐year‐old French adolescents participating as controls in the Intervention Centered on Adolescents’ Physical activity and Sedentary behavior (ICAPS). Presence of a TV set in the bedroom (TV_bedroom) and leisure activities were obtained by questionnaire. There was annual assessment of BMI, waist circumference, and body fat by bioimpedance. Results: In boys but not girls, baseline TV_bedroom was associated with higher TV/video viewing over time [odds ratio (OR) of high TV/video = 1.87; 95% confidence interval, 1.2 to 2.8] and less no‐sport club participation (OR = 0.59; 95% confidence interval, 0.35 to 1.0). Both boys and girls with baseline TV_bedroom had lower reading time (p < 0.0001 in boys; p = 0.04 in girls), while PA did not differ according to TV_bedroom for boys or for girls. For boys only, baseline TV_bedroom was associated with higher BMI (mean BMI over time 20.5 ± 0.5 vs. 19.0 ± 0.5 kg/m²; p = 0.001), waist circumference (70.9 ± 0.9 vs. 67.2 ± 0.8 cm; p < 0.001), and body fat (15.9 ± 0.9% vs. 13.5 ± 0.9%; p < 0.001), without interaction with time. These relationships remained significant after adjustment for socioeconomic status. TV/video viewing explained 26%, 42%, and 36% of the relationships of TV_bedroom with BMI, waist circumference, and body fat, respectively, while addition of other leisure activities in the models only marginally reduced the effects. Discussion: These results suggest the importance of keeping TV out of an adolescent's bedroom from an obesity prevention perspective but show gender differences.     

Central obesity as a risk factor for prostatic hyperplasia

Objective: Obesity‐related metabolic diseases may influence prostatic hyperplasia. This study examined the impact of obesity on prostate volume in men without overt obesity‐related metabolic diseases. Research Methods and Procedures: We recruited 146 men over the age of 40 years who did not have overt obesity‐related diseases, such as diabetes, impaired fasting glucose, hypertension, or dyslipidemia. Transrectal ultrasonography was performed on all subjects. The subjects were divided into three groups according to their BMI: normal (18.5 to 22.9 kg/m²), overweight (23 to 24.9 kg/m²), and obese (≥25 kg/m²), and two groups according to their waist circumference: normal waist (≤90 cm) and central obesity (>90 cm). The classification of the subgroups was based on the Asia‐Pacific criteria of obesity. We compared the prostate volume among subgroups and assessed factors related to prostatic hyperplasia. Results: Mean prostate volume was 18.8 ± 5.0, 21.8 ± 7.2, and 21.8 ± 5.6 mL in the normal, overweight, and obese groups, respectively, and was 20.0 ± 5.9 and 23.7 ± 5.3 mL in the normal waist and central obesity group, respectively. Prostate volume was significantly greater in the obese group than in the normal group (P = 0.03) and in the central obesity group compared with the normal waist group (P = 0.002). Prostate volume was positively correlated with BMI and waist circumference after adjustment for age. After adjusting for confounding factors, central obesity was an independent factor affecting prostatic hyperplasia, which was defined as a prostate volume >20 mL (odds ratio = 3.37, p = 0.037). Relative to men with both low BMI (18.5 to 22.9 kg/m²) and normal waist circumference, those with high BMI (≥25 kg/m²) and central obesity were at significantly increased risk of prostatic hyperplasia (odds ratio = 4.88, p = 0.008). However, those with high BMI (≥25 kg/m²) and normal waist circumference were not at significantly increased risk. Discussion: Prostate volume was greater in the obese and central obesity groups than in the normal group after patients with overt obesity‐related metabolic diseases were excluded. Although both BMI and waist circumference were positively correlated with prostate volume, central obesity was the only independent factor affecting prostate hyperplasia. We suggest that central obesity is an important risk factor for prostatic hyperplasia.     

The Peroxisome Proliferator‐Activated Receptor α L162V Mutation Is Associated with Reduced Adiposity

Objective: To determine the contribution of the peroxisome proliferator‐activated receptor α (PPARα) L162V mutation to the variation of several indexes of body fatness obtained from healthy adults who participated in the Quebec Family Study. Research Methods and Procedures: The PPARα L162V mutation was determined by a mismatch polymerase chain reaction method. Adiposity phenotypes were obtained by standardized anthropometric measurements, underwater weighing technique, and computed tomography. Results: For all adiposity phenotypes, subjects carrying the V162 allele had lower values compared with L162 homozygotes (HMZs) [BMI (kg/m²): 27.8 ± 7.6 vs. 26.0 ± 5.6, p < 0.05; percentage body fat: 28.5 ± 10.7 vs. 25.7 ± 10.1, p < 0.05; waist circumference (cm): 89.0 ± 18.1 vs. 85.7 ± 15.8, p = 0.07; total computed tomography abdominal fat areas (cm²): 406 ± 221 vs. 359 ± 192, p = 0.15; means ± SD for L162 HMZs vs. V162 carriers, respectively]. Differences in cross‐sectional abdominal adipose tissue areas and waist circumference were abolished after adjustment for total body fat mass. Similar trends were observed when results were analyzed by gender, although associations seemed stronger in women. The odds ratio of having a BMI above 30 kg/m² reached 1.77 (1.02; 3.07, 95% confidence intervals) for L162 HMZs. This risk could be considered marginal on an individual basis, but because 85% of the subjects are affected by this small risk, the impact on the population is important. Discussion: The PPARα V162 allele is associated with reduced adiposity and has a substantial population‐attributable risk.     

Obesity‐related Comorbidities in Obese African Americans in an Outpatient Weight Loss Program

Objective: To identify, among obese African‐American enrollees in an outpatient weight loss program, differences between those with and without obesity‐related comorbidities (ORCMs). Research Methods and Procedures: Data were from 237 obese African Americans (BMI, 30 to 50 kg/m²; 90% women) who enrolled in a 10‐week lifestyle weight loss program. Analyses compared subgroups defined by ORCM status (from medical history) on baseline characteristics, program attendance, and postprogram weight change. Results: Most participants (76%) had one or more ORCMs. Those with versus without ORCMs, respectively, were older (mean age, 45.6 vs. 37.1 years; p < 0.001), were less educated (59.2% vs. 76.6% with >12 years; p = 0.031), were more likely to perceive a physical limitation affecting activity (22.2% vs. 1.8%; p < 0.001), and had higher waist circumference (mean, 113.7 vs. 106.9 cm; p < 0.001) but not BMI (38.3 vs. 37.0 kg/m²; p = 0.095). Logistic regression analyses confirmed the independence of these associations. Having ORCMs was not associated with class attendance or return for data collection after the 10‐week program. Postprogram weight change (n = 134) was unrelated to ORCMs, but better weight loss was seen among those without perceived physical limitations (1.9 vs. 0.4 kg in those without versus with limitations; p = 0.069). Conclusion: Data from this clinical sample of obese African Americans suggest that waist circumference is relevant to ORCM status at BMI levels up to 50 kg/m². Clear indications for tailoring of treatment based on ORCM status were not identified, although the possible influence of ORCM‐related activity limitations warrants further study.     

Ethnic Differences in Visceral Adipose Tissue and Type 2 Diabetes: Filipino,African‐American,and White Women

Objective: To compare ethnic differences in visceral adipose tissue (VAT), assessed by computed tomography, and type 2 diabetes risk among 55‐ to 80‐year‐old Filipino, African‐American, and white women without known cardiovascular disease. Research Methods and Procedures: Subjects were participants in the Rancho Bernardo Study (n = 196), the Filipino Women's Health Study (n = 181), and the Health Assessment Study of African‐American Women (n = 193). Glucose and anthropometric measurements were assessed between 1995 and 2002. Results: African‐American women had significantly higher age‐adjusted BMI (29.7 kg/m²) and waist girth (88.1 cm) compared with Filipino (BMI, 25.5 kg/m²; waist girth, 81.9 cm) or white (BMI: 26.0 kg/m²; waist girth: 80.7 cm) women. However, VAT was significantly higher among Filipino (69.1 cm³) compared with white (62.3 cm³; p = 0.037) or African‐American (57.5 cm³, p < 0.001) women. VAT correlated better with BMI (r = 0.69) and waist (r = 0.77) in whites, compared with Filipino (r = 0.42; r = 0.59) or African‐American (r = 0.50; r = 0.56) women. Age‐adjusted type 2 diabetes prevalence was significantly higher in Filipinas (32.1%) than in white (5.8%) or African‐American (12.1%) women. Filipinas had higher type 2 diabetes risk compared with African Americans [adjusted odds ratio, 2.30; 95% confidence interval (CI), 1.09 to 4.86] or whites (adjusted odds ratio, 7.51; 95% CI, 2.51 to 22.5) after adjusting for age, VAT, exercise, education, and alcohol intake. Discussion: VAT was highest among Filipinas despite similar BMI and waist circumference as whites. BMI and waist circumference were weaker estimates of VAT in Filipino and African‐American women than in whites. Type 2 diabetes prevalence was highest among Filipino women at every level of VAT, but VAT did not explain their elevated type 2 diabetes risk.     

Effects of Obesity and Body Fat Distribution on Lipids and Lipoproteins in Nondiabetic American Indians: The Strong Heart Study

Objectives: To examine the relationship between obesity and lipoprotein profiles and compare the effects of total obesity and central adiposity on lipids/lipoproteins in American Indians. Research Methods and Procedures: Participants were 773 nondiabetic American Indian women and 739 men aged 45 to 74 years participating in the Strong Heart Study. Total obesity was estimated using body mass index (BMI). Central obesity was measured as waist circumference. Lipoprotein measures included triglycerides, high‐density lipoprotei in (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, apolipoprotein AI (apoAI), and apolipoprotein B (apoB). Partial and canonical correlation analyses were used to examine the associations between obesity and lipids/lipoproteins. Results: Women were more obese than men in Arizona (median BMI 32.1 vs. 29.2 kg/m²) and South Dakota and North Dakota (28.3 vs. 28.0 kg/m²), but there was no sex difference in waist circumference. Men had higher apoB and lower apoAI levels than did women. In women, when adjusted for center, gender, and age, BMI was significantly related to HDL cholesterol (r = ?0.24, p < 0.001). There was a significant but weak relation with apoAI (r = ?0.14 p < 0.001). Waist circumference was positively related to triglycerides (r = 0.14 p < 0.001) and negatively related to HDL cholesterol (r = ?0.23, p < 0.001) and apoAI (r = ?0.13, p < 0.001). In men, BMI was positively correlated with triglycerides (r = 0.30, p < 0.001) and negatively correlated with HDL cholesterol (r = ?0.35, p < 0.001) and apoAI (r = ?0.23, p < 0.001). Triglycerides increased with waist circumference (r = 0.30, p < 0.001) and HDL cholesterol decreased with waist circumference (r = ?0.36 p < 0.001). In both women and men there was an inverted U‐shaped relationship between obesity and waist with LDL cholesterol and apoB. In canonical correlation analysis, waist circumference received a greater weight (0.86) than did BMI (0.17) in women. However, the canonical weights were similar for waist (0.46) and BMI (0.56) in men. Only HDL cholesterol (?1.02) carried greater weight in women, whereas in men, triglycerides (0.50), and HDL cholesterol (?0.64) carried a large amount of weight. All the correlation coefficients between BMI, waist circumference, and the first canonical variable of lipids/lipoproteins or between the individual lipid/lipoprotein variables and the first canonical variable of obesity were smaller in women than in men. Triglycerides and HDL cholesterol showed clinically meaningful changes with BMI and waist circumference in men. All lipid/lipoprotein changes in women in relation to BMI and waist circumference were minimal. Discussion: The main lipoprotein abnormality related to obesity in American Indians was decreased HDL cholesterol, especially in men. Central adiposity was more associated with abnormal lipid/lipoprotein profiles than general obesity in women; both were equally important in men.     

Which Obesity Index Best Explains Prevalence Differences in Type 2 Diabetes Mellitus?

Objective: Obesity drives the diabetes epidemic. However, it is not known which obesity index best explains variations in type 2 diabetes mellitus prevalence across populations. Research Methods and Procedures: We analyzed three cross‐sectional studies from San Antonio, TX, (Mexican‐Americans and non‐Hispanic whites, n = 2839), Mexico City (n = 2233), and Spain (n = 2161) (age range, 35 to 64 years). We used the area under the receiver operating characteristic curve (AUC) to assess performance for identifying diabetic subjects and logistic regression analysis to examine differences in diabetes prevalence. Results: AUCs for waist circumference and BMI were similar in white subjects, but the AUC for waist circumference was greater in Mexican‐origin subjects (Mexican men, 0.594 vs. 0.549, p = 0.008; and women, 0.605 vs. 0.557, p = 0.002; Mexican‐American men, 0.648 vs. 0.600, p < 0.001; and women, 0.744 vs. 0.693, p < 0.001). The AUC for waist‐to‐height ratio tended to be greater than that for waist circumference, but statistical significance was demonstrated only in Mexican women (0.628 vs. 0.613, p = 0.044), Mexican‐American women (0.774 vs. 0.758, p < 0.001), and Spanish women (0.734 vs. 0.715, p = 0.039). No obesity index was consistently superior to the others for explaining differences in diabetes prevalence among populations. Conclusions: In white and Mexican‐origin men, waist circumference may be the preferred marker for identifying diabetic subjects on account of its simplicity; in women, waist‐to‐height ratio may be better. Differences in diabetes prevalence among these populations cannot be attributed to a single measure of obesity.     

Mediating Effects of Inflammatory Biomarkers on Insulin Resistance Associated with Obesity

Objective: Obesity is associated with elevated levels of biomarkers of inflammation and endothelial dysfunction [including C‐reactive protein (CRP), E‐selectin, and intercellular adhesion molecule‐1], as well as insulin resistance (IR) and type 2 diabetes. We tested the hypothesis that these biomarkers mediate associations among obesity, IR, and risk of diabetes. Research Methods and Procedures: We stratified 510 initially non‐diabetic women in the Nurses’ Health Study cohort into four phenotypes above/below median BMI (27 kg/m²) and waist circumference (81 cm): low BMI‐low waist (LBLW; N = 190), low BMI‐high waist (LBHW; N = 74), high BMI‐low waist (HBLW; N = 27), and high BMI‐high waist (HBHW; N = 219). Results: In models assessing associations of weight phenotype with IR [fasting insulin (FI)], adjusted for age and diabetes risk factors, mean FI was higher comparing HBHW women (13.6 μU/mL, p < 0.0001) and LBHW (11.5 μU/mL, p = 0.02) with LBLW women (8.6 μU/mL); HBLW and LBLW women were not significantly different. Differences in FI levels were most strongly attenuated after adjustment for E‐selectin comparing LBHW with LBLW women (11.7 vs. 9.7 μU/mL, p = 0.2). Discussion: In logistic regression models, LBHW predicted diabetes (risk factor‐adjusted relative risk 2.06, 1.05 to 6.40), compared with LBLW, but was no longer significant after adjustment for E‐selectin or CRP. After adjusting for CRP and E‐selectin, only HBHW and E‐selectin were significantly associated with risk of diabetes. In women with central adiposity and low BMI, endothelial dysfunction and inflammation may mediate the relationship among central fat, IR, and incident diabetes.     

Changes in Body Weight and Waist Circumference Affect Incident Hypercholesterolemia During 7 Years of Follow‐up

Objective: To assess whether changes in total and regional adiposity affect the odds for becoming hypercholesterolemic. Methods and Procedures: Changes in BMI and waist circumference were compared to self‐reported physician‐diagnosed hypercholesterolemia in 24,397 men and 10,023 women followed prospectively in the National Runners' Health Study. Results: Incident hypercholesterolemia were reported by 3,054 men and 519 women during (mean ± s.d.) 7.8 ± 1.8 and 7.5 ± 2.0 years of follow‐up, respectively. Despite being active, men's BMI increased by 1.15 ± 1.71 kg/m² and women's BMI increased by 0.96 ± 1.89 kg/m². The odds for developing hypercholesterolemia increased significantly in association with gains in BMI and waist circumferences in both sexes. A gain in BMI ≥2.4 kg/m² significantly (P < 0.0001) increased the odds for hypercholesterolemia by 94% in men and 129% in women compared to those whose BMI declined (40 and 76%, respectively, adjusted for average of the baseline and follow‐up BMI, P < 0.0001). A gain of ≥6 cm in waist circumference increased men's odds for hypercholesterolemia by 74% (P < 0.0001) and women's odds by 70% (P < 0.0001) relative to those whose circumference declined (odds increased 40% at P < 0.0001 and 49% at P < 0.01, respectively adjusted for average circumference). BMI and waist circumference at the end of follow‐up were significantly associated (P < 0.0001) with the log odds for hypercholesterolemia in both men (e.g., coefficient ± s.e.: 0.115 ± 0.011 per kg/m²) and women (e.g., 0.119 ± 0.019 per kg/m²) when adjusted for baseline values, whereas baseline BMI and circumferences were unrelated to the log odds when adjusted for follow‐up values. Discussion: These observations are consistent with the hypothesis that weight gain acutely increases the risk for hypercholesterolemia.     

Waist Circumference,BMI, and Visceral Adipose Tissue in White Women and Women of African Descent

Although waist circumference (WC) is a marker of visceral adipose tissue (VAT), WC cut‐points are based on BMI category. We compared WC‐BMI and WC‐VAT relationships in blacks and whites. Combining data from five studies, BMI and WC were measured in 1,409 premenopausal women (148 white South Africans, 607 African‐Americans, 186 black South Africans, 445 West Africans, 23 black Africans living in United States). In three of five studies, participants had VAT measured by computerized tomography (n = 456). Compared to whites, blacks had higher BMI (29.6 ± 7.6 (mean ± s.d.) vs. 27.6 ± 6.6 kg/m², P = 0.001), similar WC (92 ± 16 vs. 90 ± 15 cm, P = 0.27) and lower VAT (64 ± 42 vs. 101 ± 59 cm², P < 0.001). The WC‐BMI relationship did not differ by race (blacks: β (s.e.) WC = 0.42 (.01), whites: β (s.e.) WC = 0.40 (0.01), P = 0.73). The WC‐VAT relationship was different in blacks and whites (blacks: β (s.e.) WC = 1.38 (0.11), whites: β (s.e.) WC = 3.18 (0.21), P < 0.001). Whites had a greater increase in VAT per unit increase in WC. WC‐BMI and WC‐VAT relationships did not differ among black populations. As WC‐BMI relationship did not differ by race, the same BMI‐based WC guidelines may be appropriate for black and white women. However, if WC is defined by VAT, race‐specific WC thresholds are required.     

Adiposity in Middle‐aged Women is Associated with Genetic Taste Blindness to 6‐n‐Propylthiouracil

Objective: Taste blindness to the bitterness of 6‐n‐propylthiouracil (PROP) may be a genetic marker for food preferences and dietary choices that ultimately influence body weight. A previous study in middle‐aged women showed that those who were taste blind to PROP (i.e., nontasters) had higher BMIs than those with the greatest sensitivity to PROP (i.e., supertasters). This study tested the hypothesis that the nontaster phenotype was associated with greater adiposity in middle‐aged women. Research Methods and Procedures: Forty women with a mean BMI of 26.6 ± 1.3 kg/m² and a mean age of 41.8 ± 1.8 years were recruited from the local community. They were classified as nontasters (n = 8), medium tasters (n = 18), or supertasters (n = 14) of PROP using a filter paper screening procedure. Anthropometric measures included height, weight, body fatness, triceps skinfold thickness, and waist circumference. Dietary restraint and disinhibition were also measured to assess cognitions associated with body weight. Results: BMI was 6.2 units higher in nontaster women compared with supertaster women (29.7 ± 0.9 vs. 23.5 ± 0.9, respectively; p < 0.05). Body fatness (p < 0.01) and triceps skinfold thickness (p < 0.05) were also higher in these women. Waist circumference showed a trend in the appropriate direction. Although disinhibition was associated with greater adiposity, the relation between PROP status and adiposity was not altered after controlling for disinhibition. Discussion: The PROP nontaster phenotype was strongly associated with several measures of adiposity in middle‐aged women. These data confirm our previous findings and suggest that the PROP polymorphism may be a reliable indicator of weight gain susceptibility.     

Lipoprotein Oxidation and Plasma Vitamin E in Nondiabetic Normotensive Obese Patients

Objective: To correlate the susceptibility of low‐(LDL) and very‐low‐density lipoprotein to oxidation in vitro and the concentrations of serum antibodies against malondialdehyde‐modified LDL and plasma vitamin E with the anthropometric and laboratory characteristics of obesity. Research Methods and Procedures: A total of 75 nondiabetic, normotensive obese patients were assigned to one of four groups according to their body mass index (BMI): moderately obese (30 ≤ BMI ≤ 34.9 kg/m², n = 11), severely obese (35 ≤ BMI ≤ 39.9 kg/m², n = 20), morbidly obese (40 ≤ BMI ≤ 50 kg/m², n = 29), and very severely obese (BMI > 50 kg/m², n = 15). Results: The oxidation lag time for LDL from patients with a BMI ≥35 kg/m² was shorter than that for LDL from non‐obese controls (n = 13), whereas very‐low‐density lipoprotein oxidation lag times were not significantly different. The serum antibodies against modified LDL were similar in all groups, whereas the plasma vitamin E concentrations of obese patients were decreased (p ≤ 0.01). There was a negative correlation between LDL oxidation lag time and BMI (r = ?0.35, p = 0.0008), and between plasma vitamin E and BMI (r = ?0.53, p < 0.0001) and waist‐to‐hip ratio (r = ?0.40, p = 0.0003). Discussion: The LDL of nondiabetic, normotensive obese patients is more readily oxidized, and plasma vitamin E concentrations are low. These are both risk factors for coronary heart disease.     

Elevated serum monocyte chemoattractant protein-4 and chronic inflammation in overweight subjects

Objective: Chronic inflammation observed in obesity has been reported to be implicated in the development of atherosclerosis. We screened candidate chemokines that link chronic inflammation and obesity. Research Methods and Procedures: Japanese overweight (n = 39, BMI 28.7 ± 0.65 kg/m²) and normal‐weight (n = 24, BMI 22.3 ± 0.45 kg/m²) subjects were enrolled. Using antibody‐based protein microarray, spot intensities of monocyte chemoattractant protein (MCP)‐4, eotaxin, and eotaxin‐2 correlated with anthropometric parameters. We further measured serum concentration of these chemokines and mRNA levels in adipose tissues obtained from volunteers. Results: Serum MCP‐4 levels showed positive correlation with BMI (r = 0.318, p = 0.014), waist (r = 0.316, p = 0.018), and waist‐to‐hip ratio (WHR) (r = 0.264, p = 0.049). Furthermore, MCP‐4 correlated with homeostasis model assessment of insulin resistance (r = 0.392, p = 0.002), high‐sensitivity C‐reactive protein (hsCRP) (r = 0.350, p = 0.006). In step‐wise multiple regression analyses, hsCRP independently correlated with MCP‐4 levels. The expression of MCP‐4 mRNA in visceral adipose tissue positively correlates with BMI. Serum eotaxin levels correlate with BMI (r = 0.262, p = 0.045) and WHR (r = 0.383, p = 0.003). Serum eotaxin‐2 levels correlated with BMI (r = 0.464, p < 0.001), waist (r = 0.333, p = 0.017), and WHR (r = 0.278, p = 0.048). However, eotaxin and eotaxin‐2 levels did not show significant correlation with hsCRP. Discussion: Serum levels of MCP‐4, eotaxin, and eotaxin‐2, which belong to CC chemokine family and share CC chemokine receptor 3, correlated with BMI. These chemokines, especially MCP‐4, may be critical molecules that link obesity and chronic inflammation.     

Adiponectin and ghrelin levels and body size in normoglycemic Filipino, African-American, and white women

Objective: Prior studies have reported ethnic differences in adiponectin and ghrelin, but few have assessed the role of body size in normoglycemic women. We compared fasting adiponectin and ghrelin concentrations in normoglycemic 40‐ to 80‐year‐old Filipino, African‐American, and white women. Methods: Participants included women from the Rancho Bernardo Study (n = 143), the University of California‐San Diego Filipino Women's Health Study (n = 136), and the Health Assessment Study of African‐American Women (n = 212). A 2‐hour oral glucose tolerance test was administered; glucose, insulin, lipid, and anthropometric measurements were obtained. Fasting adiponectin and ghrelin were measured by radioimmunoassay. Results: Whites and Filipinas had similar BMI (23.7 and 24.3 kg/m², respectively), waist girth (75.6 and 77.2 cm, respectively), and total body fat (27.4 and 28.5%, respectively); African‐Americans had significantly larger BMI (28.8 kg/m²), waist girth (86.3 cm), and body fat (39.6%, p < 0.0001). Adiponectin was lower in Filipinas (8.90 µg/mL) and African‐Americans (9.67 µg/mL) compared with whites (15.6 µg/mL, p < 0.001) after adjusting for age, homeostasis model assessment of insulin resistance (HOMA‐IR), and waist‐to‐hip ratio. Compared with whites, Filipinas (β = ?5.06, p < 0.0001) and African‐Americans (β = ?6.85, p < 0.0001) had significantly lower adiponectin levels after adjusting for age, waist‐to‐hip ratio, HOMA‐IR, triglycerides, high‐density lipoprotein (HDL) cholesterol, exercise, and alcohol use. Ghrelin was significantly lower in Filipinas compared with African‐Americans (1146.9 vs. 1412.2 pg/mL, p < 0.001), and this observation persisted in multivariable analysis (β = ?245.4, p < 0.0001). Ghrelin levels did not differ between whites (1356.9 pg/mL) and either ethnic group. Discussion: Normoglycemic Filipino and African‐American women had significantly lower adiponectin concentrations than white women, and Filipinas had lower ghrelin levels than African‐Americans, independently of body size or indices of insulin resistance or lipids.     

Weight loss strategies for obese adults: personalized weight management program vs. standard care

Objective: The objective of this study was to evaluate the effect of a 32‐week personalized Polar weight management program (PWMP) compared with standard care (SC) on body weight, body composition, waist circumference, and cardiorespiratory fitness in overweight or obese adults. Research Methods and Procedures: Overweight or obese (29 ± 2 kg/m²) men and women (n = 74) 38 ± 5 years of age were randomly assigned into either PWMP (men = 20, women = 21) or SC (men = 15, women = 18). Both groups managed their own diet and exercise program after receiving the same standardized nutrition and physical activity advice. PWMP also received a weight management system with literature to enable the design of a personalized diet and exercise weight loss program. Body weight and body composition, waist circumference, and cardiorespiratory fitness were measured at weeks 0, 16, and 32. Results: Eighty percent of participants completed the 32‐week intervention, with a greater proportion of the dropouts being women (PWMP: 2 men vs. 7 women; SC: 2 men vs. 4 women). At 32 weeks, PWMP completers had significantly (p < 0.001) greater losses in body weight [6.2 ± 3.4 vs. 2.6 ± 3.6 (standard deviation) kg], fat mass (5.9 ± 3.4 vs. 2.2 ± 3.6 kg), and waist circumference (4.4 ± 4.5 vs. 1.0 ± 3.6 cm). Weight loss and fat loss were explained by the exercise energy expenditure completed and not by weekly exercise duration. Discussion: More effective weight loss was achieved after treatment with the PWMP compared with SC. The results suggest that the PWMP enables effective weight loss through tools that support self‐monitoring without the requirement of more costly approaches to program supervision.     

Anthropometric Indices and the Incidence of Hypertension: A Comparative Analysis

Objective: To investigate the association between several anthropometric measurements of obesity with the incidence of hypertension. Research Methods and Procedures: Participants were 592 individuals free of hypertension, selected at random from the community. In the baseline evaluation, they were submitted to completed measures of demographics, anthropometrics, blood pressure, and other risk factors for hypertension. Incident hypertension was defined by blood pressure equal or higher than 140/90 mm Hg or use of blood pressure‐lowering drugs. Results: During a mean follow‐up time of 5.6 ± 1.1 years, 127 developed hypertension. The hazard ratios for the development of hypertension, adjusted for age, baseline blood pressure, gender, and alcohol consumption, were 1.042 (p = 0.091) for BMI, 1.023 (p = 0.028) for waist circumference, 1.042 (p = 0.013) for waist‐to‐height ratio, 1.061 (p = 0.014) for waist‐to‐height² index, 1.079 (p = 0.022) for waist‐to‐height³ index, and 1.033 (p = 0.006) for the waist‐to‐hip ratio. Discussion: The correction of the circumference of waist for stature or hip circumference improves its performance in the prediction of the incidence of hypertension.     

Skinfolds and coronary heart disease risk factors are more strongly associated with BMI than with the body adiposity index

Objective:

A recent, cross‐sectional analysis of adults found that the hip circumference divided by height^1.5 minus 18 (the body adiposity index, BAI) was strongly correlated (r = 0.79) with percent body fat determined by dual energy X‐ray absorptiometry. The BAI was proposed as a more accurate index of body fatness than BMI. We examined whether BAI was more strongly related, than was BMI and waist circumference, to skinfold thicknesses and levels of various risk factors for coronary heart disease.

Design and Methods:

Cross‐sectional analyses of adults (n = 14,263 for skinfold thickness; n=6291 for fasting lipid levels) in the National Health and Nutrition Examination Survey (NHANES) III, 1988‐1994.

Results:

As compared with BMI and waist circumference, we found that BAI was less strongly associated with the skinfold sum and with risk factor levels. For example, correlations with the skinfold sum were r = 0.79 (BMI) vs. r = 0.70 (BAI) among men, and r = 0.86 (BMI) vs. r = 0.79 (BAI) among women; p < 0.001 for the difference between each pair of correlations. An overall index of the 7 risk factors was also more strongly associated with BMI and waist circumference than BAI in analyses stratified by sex, race‐ethnicity and age. Multivariable analyses indicated that if BMI was known, BAI provided little additional information on risk factor levels.

Conclusions:

Based on the observed associations with risk factor levels and skinfold thicknesses, we conclude that BAI is unlikely to be a better index of adiposity than BMI.     

Freshman 15: Fact or Fiction?

Objective: The objective of this study was to investigate changes in body weight, BMI, body composition, and fat distribution among freshman women during their 1st year of college. Research Methods and Procedures: Freshman women during the 2004 to 2005 academic year were recruited to participate. The initial baseline visit occurred within the first 6 weeks of the fall 2004 semester, with the follow‐up visit occurring during the last 6 weeks of the spring 2005 semester. At each visit, height, weight, BMI, waist and hip circumferences, and body composition (by DXA) were obtained. Results: One hundred thirty‐seven participants completed both the fall and spring visits. Significant (p < 0.0001) increases between the fall and spring visits were observed for body weight (58.6 vs. 59.6 kg), BMI (21.9 vs. 22.3), percentage body fat (28.9 vs. 29.7), total fat mass (16.9 vs. 17.7 kg), fat‐free mass (38.1 vs. 38.4 kg), waist circumference (69.4 vs. 70.3 cm), and hip circumference (97.4 vs. 98.6 cm), with no significant difference observed in the waist‐to‐hip ratio (0.71 vs. 0.71; p = 0.78). Discussion: Although statistically significant, changes in body weight, body composition, and fat mass were modest for women during their freshman year of college. These results do not support the purported “freshman 15” weight gain publicized in the popular media.     

Cross‐sectional Relationship of Pedometer‐Determined Ambulatory Activity to Indicators of Health

Objective: To describe the cross‐sectional relationship between an objective measure of walking (pedometer‐determined steps/day) and general indicators of health, a prior diagnosis of one or more components of the metabolic syndrome, and self‐reported occupational activity in a generally sedentary working population. Research Methods and Procedures: Steps/day were compared with previous diagnosis of one or more components of the metabolic syndrome (by self‐administered questionnaire) and with general health indicators including BMI, waist circumference, resting heart rate, and blood pressure in 182 subjects in Prince Edward Island, Canada. Study participants were volunteer employees recruited from five workplaces where, in general, the job types were moderately or highly sedentary. Results: Steps/day were 7230 ± SD 3447 for women (n = 153) and 8265 ± 2849 (n = 21) for men. Pedometer‐determined steps/day were associated inversely with BMI (r = ?0.4005, p < 0.0001) in all participants and waist circumference in females only (r = ?0.4303, p < 0.0001). There was a low correlation between steps/day and diastolic blood pressure in the whole sample (r = ?0.2140, p = 0.0383). Participants who reported a prior diagnosis of one or more components of the metabolic syndrome (hypertension, hypercholesterolemia, heart disease, or type 2 diabetes) took fewer steps/day than healthy participants (p = 0.0254). Pedometer‐determined steps/day were positively associated with self‐reported occupational activity (p = 0.0002). Discussion: Fewer steps/day are associated with increased BMI, waist circumference, diastolic blood pressure, and components of the metabolic syndrome. Low occupational activity is a contributing factor to low total ambulatory activity.     

Does a High‐protein Diet Improve Weight Loss in Overweight and Obese Children?

Objective: To evaluate the effect of a high‐protein diet on anthropometry, body composition, subjective appetite, and mood sensations in overweight and obese children attending a residential weight‐loss camp. Research Methods and Procedures: Children (120; BMI, 33.1 ± 5.5 kg/m²; age, 14.2 ± 1.9 years) were randomly assigned to either a standard or high‐protein diet group (15% vs. 22.5% protein, respectively). All children were assessed at baseline and at the end of the camp for anthropometry, body composition, blood pressure, biochemical variables (n = 27), and subjective appetite and mood sensations (n = 50). Results: Attendance at the weight‐loss camp resulted in significant improvements in most measures. Campers lost 5.5 ± 2.9 kg in body weight (p < 0.001) and 3.8 ± 5.4 kg in fat mass (p < 0.001) and reduced their BMI standard deviation score by 0.27 ± 0.1 (p < 0.001) and their waist circumference by 6.6 ± 2.8 cm (p < 0.001). Subjective sensations of hunger increased significantly over the camp duration, but no other changes in appetite or mood were observed. There were no significant differences between the two diets on any physical or subjective measures. Discussion: Weight‐loss camps are effective in assisting children to lose weight and improve on a range of health outcomes, independently of the protein content of the diet. The implications of an increase in hunger associated with weight loss needs to be considered. Further work is warranted to investigate whether higher levels of dietary protein are feasible or effective in longer‐term weight‐loss interventions of this type.